Clustering of 10 datasets (generated after performing 10 attribute weighting algorithms) into T (mesophile) and F (thermophile) classes by four different unsupervised clustering algorithms (K-Means, K-Medoids, SVC and EMC).
收藏Figshare2015-12-02 更新2026-04-29 收录
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https://figshare.com/articles/dataset/_Clustering_of_10_datasets_generated_after_performing_10_attribute_weighting_algorithms_into_T_mesophile_and_F_thermophile_classes_by_four_different_unsupervised_clustering_algorithms_K_Means_K_Medoids_SVC_and_EMC_/417559
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The actual numbers of T (mesostable) and F (thermostable) classes in the original datasets were 1544 and 513, respectively. The highest accuracy (100%) was observed when the EMC clustering method was applied to datasets generated by Correlation and Uncertainty attribute weighting algorithms that highlighted in the table.
创建时间：
2015-12-02
